In‑Process Retrieval Turns Memory Into Fast Working Memory for Language Agents
The paper shows that moving the retrieval store inside the agent’s reasoning loop and implementing it as an in‑process component (~100 µs latency) eliminates the classic memory bottleneck. Across GPT‑5‑scale models, this boosts multi‑step recall from zero to nearly five out of five, while keeping write fidelity perfect.